NeuralMidiFx: a wrapper template for deploying neural networks as VST3 plugins

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• dc.contributor.author Haki, Behzad
• dc.contributor.author Lenz, Julian
• dc.contributor.author Jordà Puig, Sergi
• dc.date.accessioned 2023-11-06T07:43:22Z
• dc.date.available 2023-11-06T07:43:22Z
• dc.date.issued 2023
• dc.description Comunicació presentada a AIMC 2023, celebrada del 30 d'agost al 1 de setembre de 2023 a Sussex, Anglaterra.
• dc.description.abstract Proper research, development and evaluation of AI-based generative systems of music that focus on performance or composition require active user-system interactions. To include a diverse group of users that can properly engage with a given system, researchers should provide easy access to their developed systems. Given that many users (i.e. musicians) are non-technical to the field of AI and the development frameworks involved, the researchers should aim to make their systems accessible within the environments commonly used in production/composition workflows (e.g. in the form of plugins hosted in digital audio workstations). Unfortunately, deploying generative systems in this manner is highly expensive. As such, researchers with limited resources are often unable to provide easy access to their works, and subsequently, are not able to properly evaluate and encourage active engagement with their systems. Facing these limitations, we have been working on a solution that allows for easy, effective and accessible deployment of generative systems. To this end, we propose a wrapper/template called NeuralMidiFx, which streamlines the deployment of neural network based symbolic music generation systems as VST3 plugins. The proposed wrapper is intended to allow researchers to develop plugins with ease while requiring minimal familiarity with plugin development.
• dc.description.sponsorship This research was partly funded by the Ministry of Science and Innovation of the Spanish Government. Agencia Estatal de Investigación (AEI). (Reference: PID2019-111403GB-I00)
• dc.format.mimetype application/pdf
• dc.identifier.citation Haki B, Lenz J, Jorda S. NeuralMidiFx: a wrapper template for deploying neural networks as VST3 plugins. In: AIMC 2023 Proceedings; 2023 Aug 30- Sep 1; Sussex, England. [s.l.]: AI Music Creativity; 2023. 18 p.
• dc.identifier.uri http://hdl.handle.net/10230/58215
• dc.language.iso eng
• dc.publisher AI Music Creativity
• dc.relation.ispartof AIMC 2023 Proceedings; 2023 Aug 30- Sep 1; Sussex, England. [s.l.]: AI Music Creativity; 2023. 18 p.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-111403GB-I00
• dc.rights Creative Commons Attribution 4.0 International License (CC-BY 4.0)
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/4.0/
• dc.title NeuralMidiFx: a wrapper template for deploying neural networks as VST3 plugins
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/publishedVersion